Data Mining and Computational Modeling of High-Throughput Screening Datasets

  • Sean Ekins, Alex M. Clark, Krishna Dole, Kellan Gregory, Andrew M. Mcnutt, Anna Coulon Spektor, Charlie Weatherall, Nadia K. Litterman, Barry A. Bunin
  • January 2018, Springer Science + Business Media
  • DOI: 10.1007/978-1-4939-7724-6_14

Data mining HTS data using machine learning

What is it about?

A book chapter on how HTS data can be used to build machine learning models and how these could assist drug discovery.

Why is it important?

We describe some literature examples of HTS efforts and databases curated around this information. We also describe computational tools for data mining. We focus on some literature kinase datasets to show how the Bayesian approach can be used.

Perspectives

Dr Sean Ekins
Collaborations in Chemistry

I think we show some nice examples of how public datasets can be put to good use and demonstrate how one kinase dataset / model can predict another from a different lab.

Read Publication

http://dx.doi.org/10.1007/978-1-4939-7724-6_14

The following have contributed to this page: Dr Sean Ekins